Since Alexander Fleming's discovery of penicillin, antibiotics have been arguably the single medical intervention that has saved more lives than any other. However, this life saving intervention is now being threatened by the problem of antibiotic resistance that is outpacing the discovery of new antibiotics, resulting in the WHO and CDC declaring antibiotic resistance as one of the greatest threats to human health. Projections include the possibility of 10 million deaths per year by 2050 with tremendous impact on the global economy in the absence of a significant shift in the current antibiotic landscape We have developed novel strategies to interface genomics and high-throughput chemical screening technologies to transform antibiotic discovery, with a focus here on the major Gram-negative pathogen Pseudomonas aeruginosa (PsA), specifically targeting its essential outer membrane proteins (OMPs) and outer membrane associated proteins (OMAPs) in order to circumvent the need for xenobiotic cytoplasmic accumulation. We have performed chemical screening in a multiplexed fashion against a pool of bar-coded, genetically engineered target-specific strains in which each of the essential OMP/OMAP target genes has been knocked-down by promoter replacement. Next generation sequencing is used to enumerate amplified barcodes to measure the census of each mutant strain in the pool in response to a small molecule. Controlled low expression of the protein of interest in each of these strains hypersensitizes them to inhibitors of the corresponding target. Importantly, this strategy has allowed us (1) to expand the numbers of small molecule candidates by identifying small molecules that would have eluded discovery if screening simply against wild-type PsA, (2) to couple whole cell screening with target-based discovery, and (3) to target essential proteins of unknown function or lack a high-throughput assay. Using this approach to target 9 essential OMP/OMAP targets in a single screen, we have identified candidates targeting the outer membrane proteins LptD and OprL, proteins required for LPS transport and cell membrane integrity, respectively. Because these targets lack robust functional assays, we have developed a high-throughput transcriptomics-driven pipeline coupled with machine learning to identify and prioritize molecules with a high likelihood of specifically inhibiting these targets. We now propose to develop the hits with completely novel mechanisms of action to lead optimization and demonstrate in vivo proof of concept.